Gene expression analyses of various tumor types (breast, lung, prostate and colon) have revealed that there exist numerous subtypes of tumors within each anatomically defined cancer. Furthermore, in some of these studies different subtypes have been linked to a particular prognosis. For example, Wigle et al, (1) and Beer et al., (2) demonstrate the existence of particular clusters of genes that are correlated with different disease-free survivals in non-small cell lung cancer. These reports establish that the molecular “make-up” of tumors, as defined by gene expression profiles, has a direct correlation to clinical endpoints such as disease free survival. These retrospective studies strongly suggest that in going forward with prospective trials there is great promise that the molecular make-up of a given tumor will be directly correlated with whether a patient will respond or not respond to a given therapy.
One means of conducting retrospective studies is by use of clinical samples, which are of two major types: frozen samples and those that have been formalin fixed and paraffin embedded. There are, however, at least three major factors to take into consideration when completing a gene expression analysis of clinical samples. First, the use of frozen samples for microarray experiments requires a large amount of tissue and in the current experimental design and methods used by most investigators, a single microarray experiment will “use up” the entire biopsied material thus significantly restricting the use of the material for post-microarray validation experiments, other microarrays with different content, or other types of studies (such as proteomic analyses).
Second, microarray studies to date generally start with a homogenized biopsy and thus have to work with only samples that are highly enriched for tumor in order to minimize the amount of cellular heterogeneity within the sample. Unfortunately, this is not the “real world” situation in a clinical trial, where there is an inability to choose which subset of biopsies will be subsequently examined. The use of laser capture microdissection (Emmert-Buck et al., 3) obviates this issue by enabling the selection and capture of the desired cell type regardless of tumor load. “Real world” samples include those where the tumor load may be extremely low (i.e., 10%), and thus the sample may be heterogeneous with respect to total number of different cell types present in the biopsy, or the sample may contain a large amount of infiltrating inflammatory cells.
Finally, routine processing of samples in the clinical setting is significantly different from that conducted in a research laboratory. In particular, for routine analysis of biopsies from a clinical setting, the tissue is processed by formalin fixation and subsequently paraffin embedded. This process is a highly efficient method that is currently the standard in pathology suites. Unfortunately, only frozen samples are being currently utilized for microarray analyses because of the general technical inability of obtaining mRNA from formalin fixed samples for global mRNA expression analysis (i.e. for hybridization to cDNA or oligo microarrays). For example, Lewis et al. (5) expressly state that loss of poly A tails from mRNA is “the main cause of failure of the reverse transcription step”.
Other attempts to utilize formalin-fixed tissue to produce cDNA for subsequent experiments have generated mixed results. For example, Karsten et al., (4) compared the use of frozen versus formalin-fixed tissues for use in cDNA microarrays via a tyramide signal amplification (TSA) system and concluded that “ . . . formalin-derived RNA was not a good substrate for cDNA synthesis and clearly did not produce reliable hybridizations in our microarray experiments”. On the other hand, Cohen et al. (9) describe the use of reverse transcription using random hexamers and real-time quantitative RT-PCR to amplify and thus detect expression of two chemokines. Similar use of reverse transcription PCR to amplify and detect expression of individual gene sequences was described by Lewis et al. (5), Lehmann et al. (6), Specht et al. (8), Masuda et al. (10), and Danenberg et al. (11). There has been no reported means to analyze gene expression at a cellular level by global amplification of extracted nucleic acids and subsequent analysis by multiplex analysis such as by use of a microarray.
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